ax = pylab.subplot(221,yscale='log')
label_axes('(a)',ax)
if noiseonly:
tags = [ 'noiseonly_n',
'noiseonly_y_normed',
'noiseonly_y' ]
else:
tags = [ 'noisy_n',
'noisy_y_normed',
'noisy_y' ]
plot_peak_func(filename(tags[0]),
color=colors[0],
label='unmasked',
scale_by_noise = False,
rmin=Mmin,
rmax=Mmax,
bins = bins)
plot_peak_func(filename(tags[1]),
color=colors[1],
label='weighted',
scale_by_noise = False,
rmin=Mmin,
rmax=Mmax,
bins = bins)
plot_peak_func(filename(tags[2]),
color=colors[2],
label='unweighted',
scale_by_noise = False,
rmin=Mmin,
ax = pylab.axes( (0.1,0.13,0.43,0.77),yscale='log')
tags = [ 'noisy_n',
'noisy_y_normed',
'noisy_y' ]
labels = ['unmasked','weighted','unweighted']
lines = []
for i in range(3):
l = plot_peak_func(filename(tags[i]),
color=colors[i],
label=labels[i],
scale_by_noise = False,
rmin=Mmin,
rmax=Mmax,
bins = bins)
lines.append(l)
leg = pylab.legend(lines[0],['E-mode','B-mode'],loc=3,frameon=False,)
pylab.legend()
ax.add_artist(leg)
pylab.xlim(0.01,0.039)
pylab.title('Without KL')
ax = pylab.axes( (0.53,0.13,0.43,0.77),yscale='log')
tags = ['900_n_a0.15y','900_y_a0.15y']